* Removing last dims constraints of seq_pad and seq_unpad test=develop

* fix test_layer api code test=develop

* fix sequence_pad_op.cc conflict test=develop

* remove test_analyzer_mm_dnn test=develop

* fix vectorize bug test=develop

* fix vectorize<int> test=develop

* Add float16 support to `sync_batch_norm_op`

test=develop

* Add test for sync_bn with FP16 input

test=develop

* Remove constraint that last dimension is forced to be 1 by add
lookup_table_v2 test=develop

* modify into PADDLE_ENFORCE_CUDA_SUCCESS test=develop

* Revert "modify into PADDLE_ENFORCE_CUDA_SUCCESS test=develop"

This reverts commit 8a960bfc61e51aa27c3c529df8fb90b93ebd19f9.

* move api into fluid.embedding test=develop

* fix example code test=develop

* move one_hot into fluid.one_hot

* modify api.spec test=develop

* fix loss shape test=develop

* support change shuffle thread num
* support change train thread num
* fix receive shuffle data of each channel
* data norm stop gradient
* add check thread_tensor type and root_tensor type when merge metric
* remove sleep in shuffle, add config
* add config of pslib client to client communication
* fix xbox str
* add data norm op testcase
* add flush in trainer finalize

* give warnings when save a model without any parameters test=develop

* delete one line comment test=develop

* add py_reader combination unittest,test=develop

* follow huihuang's comments, test=develop

* make OpTest check grad inplace even if forward has no inplace, test=develop

* do not run PE when enable_inplace is False, test=develop

* add conv3d cuda kernel for float16 type, test=develop

* refactor OpTest for inplace, test=develop

* add comments, test=develop

* add recompute based checkpoints methods for large batch training
test=develop

* add append_backward_with_forward_recomputation
test=develop

* refine optimizer
test=develop

* update backward and optimizer
test=develop

* make Variable usable
test=develop

* add recompute code

* refine optimizer
test=develop

* refine addup _append_backward_ops_with_checkpoints_
1) for recompute part, just cache the grad_op_desc without appending to block
2) before appending grad_op_desc to backward part, addup_repetitive_vars, remove unused branch
test=develop

* make method private

* add recompute strategy into DistributedStrategy
test=develop

* checkpoint version3
test=develop

* remove some print information
test=develop

* remove unused sumop
test=develop

* try to fix recompute with graph building modules

* add input names to vars should be held

* add memory debug tool

* backup backward

* Fix bugs

* add backward desc for op not in any segments

* add exception info for sub_block

test=develop

* modify code style

test=develop

* modify code style

test=develop

* remove print functions

test=develop

* add API spec

test=develop
test=document_preview

* make Recompute a child class of Optimizer

test=develop
test=document_preview

* add API spec

test=develop
test=document_preview

* modify API spec

test=develop
test=document_preview

* add document for Recompute

test=develop
test=document_preview

* change API doc of Rcompute

test=develop
test=document_preview

* code cleaning

test=develop
test=document_preview

* modify API spec

* fix bugs when segments hold no element

* add testcase for Recompute Optimizer

test=develop
test=document_preview

* add test for apply_gradient, and code cleaning

test=develop
test=document_preview

* add test case for load function

* enable CI

test=develop
test=document

* add test case

test=develop
test=document_preview

* add sample code for 4 function of recompute optimizer

test=develop
test=document_preview

* optimize the error information when the input for while op has a wrong shape test=develop

* add mse_loss op

* move tree_conv to fluid.contrib.layers

test=develop

* update API.spec for tree_conv

test=develop

* update tree_conv api to increase unit coverage

test=develop

* unify DataLoader APIs, test=develop

* integrate iterable CPU Dataset, test=develop
add GPU dataset supporting, test=develop

* add unittests for dataset, test=develop

* add more docs to dataloader apis, test=develop, test=document_preview

* refine doc, test=develop

* refine doc again, test=develop

* increase coverage, test=develop

* optimize cloud rolemaker, test=develop

* add instance norm op

* Initial, functional commit

* Clean commit related files
test=develop

* refactor dygraph,test=develop

* fix failed unittest,test=develop

* polish code,test=develop

* check windows ci error,test=develop
try to fix windows ci error by np.allclose,test=develop

* polish vlog and profiler, test=develop

* try to fix preceding ops order,test=develop

* test transformer in windows ci, test=develop

* use python c-api to speed up tracer.trace,test=develop

* test=develop, fix docker with paddle nccl problem

* test=develop, add ut for debug string and gradient_accumulator

* test=develop, add tests for layer/gradient_accumulator/prepared_op

* test=develop, fix complie error for test_prepared_op

* test=develop, add more ut for dygraph

* test=develop, create API.spec for dygraph api change

* test=develop, refoctor name to make it easier to understand

* test=develop, refoctor name to make it easier to understand

* test=develop, fix multi-gpu failed problem , add Tracer tests, change PADDLEENFORCE to PADDLEENFORCE_EQ

* test=develop, fix ut failed on parallel se-resnext

* test=develop, change one more PADDLE_ENFORCE

* support auto prune in dygraph mode

* test=develop, support auto prune

* test=develop, merge develop conflict

* test=develop, fix test_layer and test_tracer ut

* test=develop, fix bug which may cause stop_gradient disabled with a list of backward inputs

* support 2-level lod of input in sequence_pool test=develop

* fix lod level bug in .cu test=develop

1. group_norm support data_layout=NHWC
2. modified doc of group_norm

modified interpolate_op to support tensor attribute

1. the parameter out_shape of image_resize、resize_nearest/bilinear/trilinear can be a list or a 1-D tensor variable. If a list, each element can be an integer or a tensor variable with shape: [1].

2. the parameter scale of above Ops can be a 1-D tensor variable.
modified document of image_resize, resize_nearest, resize_bilinear, resize_trilinear and add some code example.

add crop_tensor op. The main difference with crop is :

1. If the argument shape is a list, each element is an integer or a tensor variable with shape: [1]. This way is suitable for the case that the shape may be changed each iteration.

2. If the argument shape is a variable. Its rank must be 1. In crop op, the rank of shape must be the same as x

offsets can be a list, in which each element is an integer or a tensor variavle with shape: [1].

* Remove constraint that last dimension is forced to be 1 in cross_entropy
test=develop

* modify labels last dims test=develop

* add precise roi pooling op test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* test=develop

* detail the description test=develop

* test=develop

* elaborate the doc for return type test=develop

* test=develop

* Add fc_elementwise_layernorm_fuse pass and unittest.

* Add fused_fc_elementwise_layernorm op and its GPU kernel.
test=develop

* Apply fc_elementwise_layernorm_fuse_pass to GPU inference.

* Add the setting of attrs in the definition of binary_op.
test=develop

* Add comment.

* Implement the unittest.
test=develop

* Change the unittest name of layer_norm.
test=develop

distribute.launch use poll to query subprocess

* Fix std::ostream& operator<<(std::ostream& os, const Tensor& t)
test=develop

* Fix test_dygraph_mnist_fp16
test=develop

* disable test_dygraph_mnist_fp16
test=develop

* revert tensor_util.cc fix
test=develop

* strided_slice op basic function test=develop

* test=develop rewrite and fix

* fix bug test=develop

* fix for the PADDLE_ENFORCE usage

* add some unit testw

* fix for the aip  test and copright and fix test=develop

* fix API.spec test=develop

* fix API.spec test=develop

* add axis parameter test=develop

* fix for the build error test=develop

* fix python api  test=develop

* fix the build test=develop

* fix build test=develop

* fix API spec test=develop

* test=develop add some comment and single op test

* fix API spece test=develop

* fix test=develop

* fix test=develop

* fix api test=develop

* fix api test=develop

* fix API.spec test=develop

* fix typo test=develop

* fix API.spec test=develop

* fix API typo test=develop

* fix doc and API.spec test=develop

* fix memory reuse bug on feeding variables, test=develop

* add comments to reference count members, test=develop

* add deformable conv v1 op, test=develop

* Add fp16 support for dygraph
test=develop

* Add unit test
test=develop

* update OpTest to support double grad inplace check, test=develop

* keep consistency of _calc_output function, test=develop

improve pow op according to reviews:
1. Delete unnecessary judgement statements in PowGradOpDescMaker;
2. Improve test of test_api;

overload GetKernelTypeForVar

add stop_gradient=True when attr(factor) is tensor Variable, change examples in API pow.
test=develop,test=document_preview

add support parameter inference when argument shape is a list containing integer and tensor variable;
test=develop

fix reshape op according to reviews:
1. improve or message;
2. improve test of test_api.
test=develop,test=document_preview

fix reshape op: Add error message in nn.py, test=develop

add stop_gradient=True when attr(shape) is tensor Variable.
change examples in API reshape.
test=develop,test=document_preview

add support parameter inference when arguments starts or ends is a list containing integer and tensor variable;
test=develop,test=document_preview

improve slice op according to review(from hongyu). test=develop

fix slice op according to review: infer_flags, test=develop

fix slice op: improve overload operator __getitem__ to support attrs(starts and ends) are Variable.
test=develop,test=document_preview

fix test_slice_op: add TestSliceOp_decs_dim_6 to resolve conflict with test_slice_ngraph_op. test=develop

add stop_gradient=True when attr(starts) or attr(ends) is tensor Variable.
test=develop,test=document_preview